The Property Records Industry Association is conducting a webinar on May 17th. The presentation will be led by Jerry Lewallen and Sharon Martin. They will be discussing, answering questions, and talking the importance of predictable fees.
You have a software package that relies on optical character recognition (OCR) to classify, pick up words, numbers or phrases from a document. As long as the quality of the document is mostly clean, everything works well. However, what happens when the document arrives and the quality is simply, not good? Does the software give up and run away with its tail between its legs? Are there any options to classify or capture anything on these documents?
First came Alien, then Predator, followed by Alien versus Predator. The Alien series chronicles the battle between humans and a mysterious lifeform whose lifecycle has just begun. Predator was based on an extraterrestrial hunter stalking commandos in Central America and the citizens of Los Angeles. When the two series merged, it featured an epic battle between the two legends.
Document formatting and quality can have a dramatic effect on OCR and rules accuracy when data capture is concerned. The 5 examples shown below are meant to educate a potential or current data capture user on what can cause accuracy to rise or fall. Although sometimes it’s hard or impossible to correct the issues that cause accuracy to fall, there are generally steps that can be taken to help prevent them.
Early 2017, the Government Business Council and Veritas did extensive research and built a survey to figure out if federal organizations are living out “principles of transparency, participation, and collaboration.”